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refactor(network.py): annotacte activation functions

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Loïc GUEZO
2026-01-18 18:23:14 +01:00
parent 08cbb807f9
commit 17be224d25
2 changed files with 7 additions and 8 deletions
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9
network.py
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@@ -1,13 +1,12 @@
import math import math
import random import random
# transform all numbers between 0 and 1 def sigmoid(x: float) -> float:
def sigmoid(x):
return 1 / (1 + math.exp(-x)) return 1 / (1 + math.exp(-x))
# sigmoid's derivation
def sigmoid_deriv(x): def sigmoid_deriv(x: float) -> float:
y = sigmoid(x) y: float = sigmoid(x)
return y * (1 - y) return y * (1 - y)
# neuron class # neuron class

6
nnetwork.ipynb
View File

@@ -224,7 +224,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": null,
"id": "f6de25ea", "id": "f6de25ea",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@@ -284,7 +284,7 @@
" # update bias: bias -= learning_rate * dC/dy * dy/dz * dz/db\n", " # update bias: bias -= learning_rate * dC/dy * dy/dz * dz/db\n",
" self.bias -= learning_rate * dcost_dy * dy_dz * dz_db\n", " self.bias -= learning_rate * dcost_dy * dy_dz * dz_db\n",
"\n", "\n",
" # return gradient vector len(input) dimension\n", " # return gradient vector len(weight) dimension\n",
" return [dcost_dy * dy_dz * w for w in self.weight]" " return [dcost_dy * dy_dz * w for w in self.weight]"
] ]
}, },
@@ -353,7 +353,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.13.4" "version": "3.13.5"
} }
}, },
"nbformat": 4, "nbformat": 4,